THIS FUNCTION IS DEPRECATED. It will be removed in a future version.
Instructions for updating:
Please switch to tf.metrics.false_positives. Note that the order of the labels and predictions arguments has been switched.

If weights is None, weights default to 1. Use weights of 0 to mask values.

Args:

predictions: The predicted values, a Tensor of arbitrary dimensions. Will
be cast to bool.

labels: The ground truth values, a Tensor whose dimensions must match
predictions. Will be cast to bool.

weights: Optional Tensor whose rank is either 0, or the same rank as
labels, and must be broadcastable to labels (i.e., all dimensions
must be either 1, or the same as the corresponding labels
dimension).

metrics_collections: An optional list of collections that the metric
value variable should be added to.

updates_collections: An optional list of collections that the metric update
ops should be added to.

name: An optional variable_scope name.

Returns:

value_tensor: A Tensor representing the current value of the metric.

update_op: An operation that accumulates the error from a batch of data.

Raises:

ValueError: If predictions and labels have mismatched shapes, or if
weights is not None and its shape doesn't match predictions, or if
either metrics_collections or updates_collections are not a list or
tuple.